Our objective is to provide a computer technology for keeping radiologists and other medical scientists and practitioners in their tasks of acquiring, analyzing, storing and transmitting medical images. Our current emphasis is on computer-aided diagnosis of chest radiographs and mammograms. We are using pseudo-inverse digital filters for recapturing the details that are blurred by distributed focal spots in magnification radiography. We are developing a procedure for detecting and representing blood vessels in chest radiographs. We are developing a set of textural features and an associated trainable decision function for classifying lesions in mammograms. We are carrying out a clinical test on the mammograms of 16 subjects, using our textural features and decision function. We are developing a new model of texture and textural features based on the theory of Markov random fields. We are constructing a computer program that reconstructs the rib cage from two slightly magnified radiographic images of the chest. We are constructing an interactive radiologist-controlled system for enhancing the contrast of radiographs and for producing graphically illustrated diagnostic reports of radiographs. We are developing a computerized consultant for the diagnosis of chest radiographs.